Low Complexity Blind Equalization for OFDM Systems with General Constellations

This paper proposes a low-complexity algorithm for blind equalization of data in OFDM-based wireless systems with general constellations. The proposed algorithm is able to recover data even when the channel changes on a symbol-by-symbol basis, making it suitable for fast fading channels. The proposed algorithm does not require any statistical information of the channel and thus does not suffer from latency normally associated with blind methods. We also demonstrate how to reduce the complexity of the algorithm, which becomes especially low at high SNR. Specifically, we show that in the high SNR regime, the number of operations is of the order O(LN), where L is the cyclic prefix length and N is the total number of subcarriers. Simulation results confirm the favorable performance of our algorithm

Joint data detection and channel estimation for OFDM systems

We develop new blind and semi-blind data detectors and channel estimators for orthogonal frequency-division multiplexing (OFDM) systems. Our data detectors require minimizing a complex, integer quadratic form in the data vector. The semi-blind detector uses both channel correlation and noise variance. The quadratic for the blind detector suffers from rank deficiency; for this, we give a low-complexity solution. Avoiding a computationally prohibitive exhaustive search, we solve our data detectors using sphere decoding (SD) and V-BLAST and provide simple adaptations of the SD algorithm. We consider how the blind detector performs under mismatch, generalize the basic data detectors to nonunitary constellations, and extend them to systems with pilots and virtual carriers. Simulations show that our data detectors perform well

New Full-Diversity Space-Time-Frequency Block Codes with Simplified Decoders for MIMO-OFDM Systems

Multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) is known as a promising solution for wideband wireless communications. This is why it has been considered as a powerful candidate for IEEE 802.11n standard. Numerous space-frequency block codes (SFBCs) and space-time- frequency block codes (STFBCs) have been proposed so far for implementing MIMO-OFDM systems. In this paper, at first we propose new full-diversity STFBCs with high coding gain in time-varying channels; the construct method for this structure is using orthogonal space-time block code for any arbitrary number of transmit antenna and then we propose a decoder with linear complexity for our proposed coding scheme. Simulation results verify that the proposed STFBCs outperform other recently published STFBCs

Iterative joint channel and data estimation for rank-deficient MIMO-OFDM

In this paper we propose a turbo-detected multi-antenna-multi-carrier receiver scheme. Following the philosophy of the turbo processing, our turbo MIMO-OFDM receiver comprises a succession of detection modules, namely the channel estimator, the space-time detector and the decoder, which iteratively exchange soft bit-related information and thus facilitate a substantial improvement of the overall system performance. In this paper we analyze the achievable performance of the iterative system proposed with the aim of documenting the various design trade-offs, such as the achievable error-rate performance, the attainable data-rate as well as the associated computational complexity. Specifically, we report a virtually error-free performance for a rate-1/2 turbo-coded 8x8-QPSK-OFDM system, exhibiting an effective throughput of 8*2/2=8 bits/sec/Hz and having a pilot overhead of only 10%, at SNR of 7.5dB and normalized Doppler frequency of 0.003, which corresponds to a mobile terminal speed of about 65 km/h

Dispensing with Channel Estimation…

In this article, we investigate the feasibility of noncoherent detection schemes in wireless communication systems as a low-complexity alternative to the family of coherent schemes. The noncoherent schemes require no channel knowledge at the receiver for the detection of the received signal, while the coherent schemes require channel inherently complex estimation, which implies that pilot symbols have to be transmitted resulting in a wastage of the available bandwidth as well as the transmission power

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Blind Receiver Design for OFDM Systems Over Doubly Selective Channels

We develop blind data detectors for orthogonal frequency-division multiplexing (OFDM) systems over doubly selective channels by exploiting both frequency-domain and time-domain correlations of the received signal. We thus derive two blind data detectors: a time-domain data detector and a frequency-domain data detector. We also contribute a reduced complexity, suboptimal version of a time-domain data detector that performs robustly when the normalized Doppler rate is less than 3%. Our frequency-domain data detector and suboptimal time-domain data detector both result in integer least-squares (LS) problems. We propose the use of the V-BLAST detector and the sphere decoder. The time-domain data detector is not limited to the Doppler rates less than 3%, but cannot be posed as an integer LS problem. Our solution is to develop an iterative algorithm that starts from the suboptimal time-domain data detector output. We also propose channel estimation and prediction algorithms using a polynomial expansion model, and these estimators work with data detectors (decision-directed mode) to reduce the complexity. The estimators for the channel statistics and the noise variance are derived using the likelihood function for the data. Our blind data detectors are fairly robust against the parameter mismatch